scholarly journals Indoor Traveling Salesman Problem (ITSP) Path Planning

2021 ◽  
Vol 10 (9) ◽  
pp. 616
Author(s):  
Jinjin Yan ◽  
Sisi Zlatanova ◽  
Jinwoo (Brian) Lee ◽  
Qingxiang Liu
Keyword(s):  
Path Planning ◽  
Traveling Salesman Problem ◽  
Indoor Navigation ◽  
Traveling Salesman ◽  
Shopping Mall ◽  
Navigation Systems ◽  
Quick Response ◽  
Navigation Path ◽  
Shortest Distance ◽  
Increasing Demand

With the growing complexity of indoor living environments, people have an increasing demand for indoor navigation. Currently, navigation path options in indoor are monotonous as existing navigation systems commonly offer single-source shortest-distance or fastest paths. Such path options might be not always attractive. For instance, pedestrians in a shopping mall may be interested in a path that navigates through multiple places starting from and ending at the same location. Here, we name it as the indoor traveling salesman problem (ITSP) path. As its name implies, this path type is similar to the classical outdoor traveling salesman problem (TSP), namely, the shortest path that visits a number of places exactly once and returns to the original departure place. This paper presents a general solution to the ITSP path based on Dijkstra and branch and bound (B&B) algorithm. We demonstrate and validate the method by applying it to path planning in a large shopping mall with six floors, in which the QR (Quick Response) codes are assumed to be utilized as the indoor positioning approach. The results show that the presented solution can successfully compute the ITSP paths and their potentials to apply to other indoor navigation applications at museums or hospitals.

scholarly journals ON SAMPLING BASED METHODS FOR THE DUBINS TRAVELING SALESMAN PROBLEM WITH NEIGHBORHOODS

2015 ◽  
Vol 2 (2) ◽  
pp. 57-61
Author(s):  
Petr Váňa ◽  
Jan Faigl
Keyword(s):  
Path Planning ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Computational Time ◽  
Solution Quality ◽  
Goal Region ◽  
Dubins Vehicle ◽  
Proposed Modification ◽  
Dubins Traveling Salesman Problem

In this paper, we address the problem of path planning to visit a set of regions by Dubins vehicle, which is also known as the Dubins Traveling Salesman Problem Neighborhoods (DTSPN). We propose a modification of the existing sampling-based approach to determine increasing number of samples per goal region and thus improve the solution quality if a more computational time is available. The proposed modification of the sampling-based algorithm has been compared with performance of existing approaches for the DTSPN and results of the quality of the found solutions and the required computational time are presented in the paper.

scholarly journals TWO NEW PEDESTRIAN NAVIGATION PATH OPTIONS BASED ON SEMI-INDOOR SPACE

2020 ◽  
Vol VI-4/W1-2020 ◽  
pp. 175-182
Author(s):  
J. Yan ◽  
S. Zlatanova ◽  
A. A. Diakite
Keyword(s):  
Path Selection ◽  
Selection Strategy ◽  
Navigation Systems ◽  
Indoor Space ◽  
Pedestrian Navigation ◽  
Navigation Path ◽  
Shortest Distance ◽  
Making Choices ◽  
Navigation Experience ◽  
Indoor Spaces

Abstract. Navigation is very critical for our daily life, especially when we have to go through the unfamiliar areas where the spaces are very complex, such as completely bounded (indoor), partially bounded (semi-indoor and/or semi-outdoor), entirely open (outdoor), or combined. Current navigation systems commonly offer the shortest distance/time path, but it is not always appropriate for some situations. For instance, on a rainy day, a path with as many places that are covered by roofs/shelters is more attractive. However, current navigation systems cannot provide such kinds of navigation paths, which can be explained by that they lack information about such roofed/sheltered-covered spaces. This paper proposes two roofed/sheltered navigation path options by employing semi-indoor spaces in the navigation map: (i) the Most-Top-Covered path (MTC-path) and (ii) path to the Nearest sI-space from departure (NSI-path). A path selection strategy is introduced to help pedestrians in making choices between the two new path options and the traditional shortest path. We demonstrate and validate the research with path planning on two navigation cases. The results show the two path options and the path selection strategy bring in new navigation experience for humans.

scholarly journals Genetic Algorithm for Combinatorial Path Planning: The Subtour Problem

2011 ◽  
Vol 2011 ◽  
pp. 1-31 ◽  
Author(s):  
Giovanni Giardini ◽  
Tamás Kalmár-Nagy
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Local Search ◽  
Traveling Salesman Problem ◽  
Optimal Strategy ◽  
Numerical Experiments ◽  
Solution Method ◽  
Autonomous Systems ◽  
Traveling Salesman ◽  
Optimal Solutions

The purpose of this paper is to present a combinatorial planner for autonomous systems. The approach is demonstrated on the so-called subtour problem, a variant of the classical traveling salesman problem (TSP): given a set of possible goals/targets, the optimal strategy is sought that connects goals. The proposed solution method is a Genetic Algorithm coupled with a heuristic local search. To validate the approach, the method has been benchmarked against TSPs and subtour problems with known optimal solutions. Numerical experiments demonstrate the success of the approach.

scholarly journals Heuristics for Two Depot Heterogeneous Unmanned Vehicle Path Planning to Minimize Maximum Travel Cost

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2461 ◽  
Author(s):  
Jungyun Bae ◽  
Woojin Chung
Keyword(s):  
Path Planning ◽  
Traveling Salesman Problem ◽  
Target Location ◽  
Travel Cost ◽  
Unmanned Vehicles ◽  
Traveling Salesman ◽  
Planning Problem ◽  
Travel Costs ◽  
Primal Dual ◽  
Multiple Depot

A solution to the multiple depot heterogeneous traveling salesman problem with a min-max objective is in great demand with many potential applications of unmanned vehicles, as it is highly related to a reduction in the job completion time. As an initial idea for solving the min-max multiple depot heterogeneous traveling salesman problem, new heuristics for path planning problem of two heterogeneous unmanned vehicles are proposed in this article. Specifically, a task allocation and routing problem of two (structurally) heterogeneous unmanned vehicles that are located in distinctive depots and a set of targets to visit is considered. The unmanned vehicles, being heterogeneous, have different travel costs that are determined by their motion constraints. The objective is to find a tour for each vehicle such that each target location is visited at least once by one of the vehicles while the maximum travel cost is minimized. Two heuristics based on a primal-dual technique are proposed to solve the cases where the travel costs are symmetric and asymmetric. The computational results of the implementation have shown that the proposed algorithms produce feasible solutions of good quality within relatively short computation times.

scholarly journals INDOOR NAVIGATION AND MAPPING: PERFORMANCE ANALYSIS OF UWB-BASED PLATFORM POSITIONING

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 549-555
Author(s):  
A. Masiero ◽  
H. Perakis ◽  
J. Gabela ◽  
C. Toth ◽  
V. Gikas ◽  
...  
Keyword(s):  
Wide Band ◽  
Indoor Navigation ◽  
Operating Conditions ◽  
Navigation Systems ◽  
Positioning Systems ◽  
Localization And Mapping ◽  
Wide Range ◽  
Increasing Demand ◽  
Slam Algorithm ◽  
Tof Camera

Abstract. The increasing demand for reliable indoor navigation systems is leading the research community to investigate various approaches to obtain effective solutions usable with mobile devices. Among the recently proposed strategies, Ultra-Wide Band (UWB) positioning systems are worth to be mentioned because of their good performance in a wide range of operating conditions. However, such performance can be significantly degraded by large UWB range errors; mostly, due to non-line-of-sight (NLOS) measurements. This paper considers the integration of UWB with vision to support navigation and mapping applications. In particular, this work compares positioning results obtained with a simultaneous localization and mapping (SLAM) algorithm, exploiting a standard and a Time-of-Flight (ToF) camera, with those obtained with UWB, and then with the integration of UWB and vision. For the latter, a deep learning-based recognition approach was developed to detect UWB devices in camera frames. Such information is both introduced in the navigation algorithm and used to detect NLOS UWB measurements. The integration of this information allowed a 20% positioning error reduction in this case study.

Evaluation of an Accessible, Real-Time, and Infrastructure-Free Indoor Navigation System by Users Who Are Blind in the Mall of America

2019 ◽  
Vol 113 (2) ◽  
pp. 140-155 ◽  
Author(s):  
Nicholas A. Giudice ◽  
William E. Whalen ◽  
Timothy H. Riehle ◽  
Shane M. Anderson ◽  
Stacy A. Doore
Keyword(s):  
Real Time ◽  
Navigation System ◽  
Memory Load ◽  
The United States ◽  
Indoor Navigation ◽  
Shopping Mall ◽  
Navigation Systems ◽  
Route Guidance ◽  
Indoor Navigation System ◽  
The Impact

Introduction: This article describes an evaluation of MagNav, a speech-based, infrastructure-free indoor navigation system. The research was conducted in the Mall of America, the largest shopping mall in the United States, to empirically investigate the impact of memory load on route-guidance performance. Method: Twelve participants who are blind and 12 age-matched sighted controls participated in the study. Comparisons are made for route-guidance performance between use of updated, real-time route instructions (system-aided condition) and a system-unaided (memory-based condition) where the same instructions were only provided in advance of route travel. The sighted controls (who navigated under typical visual perception but used the system for route guidance) represent a best case comparison benchmark with the blind participants who used the system. Results: Results across all three test measures provide compelling behavioral evidence that blind navigators receiving real-time verbal information from the MagNav system performed route travel faster (navigation time), more accurately (fewer errors in reaching the destination), and more confidently (fewer requests for bystander assistance) compared to conditions where the same route information was only available to them in advance of travel. In addition, no statistically reliable differences were observed for any measure in the system-aided conditions between the blind and sighted participants. Posttest survey results corroborate the empirical findings, further supporting the efficacy of the MagNav system. Discussion: This research provides compelling quantitative and qualitative evidence showing the utility of an infrastructure-free, low-memory demand navigation system for supporting route guidance through complex indoor environments and supports the theory that functionally equivalent navigation performance is possible when access to real-time environmental information is available, irrespective of visual status. Implications for designers and practitioners: Findings provide insight for the importance of developers of accessible navigation systems to employ interfaces that minimize memory demands.

scholarly journals Top-Bounded Spaces Formed by the Built Environment for Navigation Systems

2019 ◽  
Vol 8 (5) ◽  
pp. 224 ◽  
Author(s):  
Jinjin Yan ◽  
Abdoulaye A. Diakité ◽  
Sisi Zlatanova ◽  
Mitko Aleksandrov
Keyword(s):  
Built Environment ◽  
Optimal Path ◽  
Use Case ◽  
Navigation Systems ◽  
Space Model ◽  
Navigation Path ◽  
Shortest Distance ◽  
Systems Models ◽  
The Right

Navigation systems help agents find the right (optimal) path from the origin to the desired destination. Current navigation systems mainly offer the shortest (distance or time) path as the default optimal path. However, under certain circumstances, having a least-top-exposed path can be more interesting. For instance, on a rainy day, a path with as many places as possible covered by roofs/shelters is more attractive and pragmatic, since roofs/shelters can offer protection from rain. In this paper, we name environments that covered by roofs/shelters but not completely enclosed like indoors as “top-bounded environments/spaces” (e.g., porches), which are generally formed by built structures. This kind of space is completely missing in current navigation models and systems. Thus, we investigate how to use it for space-based navigation. After proposing a definition, a space model, and attributes of top-bounded spaces, we introduce a projection-based approach to generate them. Then, taking a pedestrian as an example agent, we select generated spaces considering whether the agent can visit/use the identified spaces. Finally, examples and a use case study demonstrate that our research can help to include top-bounded spaces in navigation systems/models. More navigation path types (e.g., least-top-exposed) can be offered for different agents (such as pedestrians, drones or robots).

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